{"id":1181606,"date":"2026-08-06T00:00:00","date_gmt":"2026-08-06T07:00:00","guid":{"rendered":"https:\/\/research.codeghost.online\/en-us\/research\/?post_type=msr-research-item&#038;p=1181606"},"modified":"2026-08-13T09:35:05","modified_gmt":"2026-08-13T16:35:05","slug":"responsible-use-of-artificial-intelligence-and-machine-learning-for-food-security-early-warning-systems","status":"publish","type":"msr-research-item","link":"https:\/\/research.codeghost.online\/en-us\/research\/publication\/responsible-use-of-artificial-intelligence-and-machine-learning-for-food-security-early-warning-systems\/","title":{"rendered":"Responsible use of artificial intelligence and machine learning for food security early warning systems."},"content":{"rendered":"\n\n\n<p class=\"wp-block-paragraph\">Artificial intelligence and machine learning are already enhancing food security early warning systems by improving data collection, event monitoring and forecasting. However, to avoid costly errors, artificial intelligence and machine learning should be applied selectively alongside expert oversight, robust governance and transparent practices to maintain accountable and effective humanitarian decision-making.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence and machine learning are already enhancing food security early warning systems by improving data collection, event monitoring and forecasting. However, to avoid costly errors, artificial intelligence and machine learning should be applied selectively alongside expert oversight, robust governance and transparent practices to maintain accountable and effective humanitarian decision-making.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"text","value":"Weston B. 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